Category Archives: Biological physics

Computing hell

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SFChas “Let us always keep before our mind’s eye an overheated and glowing stove and inside a naked man, supine, who will never be released from such pain. Does not his pain appear unbearable to us for even a single moment?”

Thus wrote the 15th-century theologian and mystic Denis the Carthusian in his tract about the Last Judgment, De quatuor hominis novissimus. When I encountered the passage in Johan Huizinga’s The Waning of the Middle Ages (1919), another, more recent book came to mind: Iain M. Banks’s science fiction novel, Surface Detail (2010).

The novel’s action takes place in our galaxy in AD 2970. By then, technology has reached the point that a person’s consciousness can be recorded and inserted into virtual, simulated worlds—including hells of such fiendishly imaginative gruesomeness that I’ll refrain from quoting a description. Some of the galaxy’s species support the hells as an effective means to discourage bad behavior; others decry them as a moral outrage. To settle the hells’ disputed existence, the various interested species have agreed to abide by the outcome of a vast simulated war game.

Virtual, simulated worlds have been featured in science fiction for some time. My first encounter with them—and perhaps yours, too—was in William Gibson’s Neuromancer (1984). The novel’s complex, thrilling plot involves two powerful and resourceful artificial intelligences and a cast of drug-addicted hackers, former special operations soldiers, plutocratic industrialists, and cyberpunk ninjas.

permutation-city

Gibson favored a mostly metaphorical description of computed reality. In Permutation City (1994), Greg Egan delves in more technical detail into the philosophical questions of simulated afterlives. Presciently, in Egan’s near-future world, computing power is available in abundance via the cloud. With such resources, Paul Durham, a computer scientist and entrepreneur, proposes to create a self-sustaining virtual world where scanned consciousnesses can live for eternity.

In reality, though, how likely is the prospect of scanning a consciousness and uploading it into a virtual world? Human brains contain 1011 neurons that form 1015 interconnections. Storing a static map of something that big isn’t beyond current technology. CERN has already amassed 2 × 1017 bytes of data from the Large Hadron Collider.

The bigger technological challenge, I think, lies in generating the map in the first place. Conceivably, neuroscientists could discover a modest set of principles that embody how our brains are networked, obviating the task of mapping individual neurons. But if they can’t, every neuron and synapse would have to be located. Super-resolution techniques such as Stochastic Optical Reconstruction Microscopy (STORM) and Photoactivation Localization Microscopy (PALM) can already map fluorescently tagged molecules with a spatial resolution of a few tens of microns, but only—so far—in samples just a few millimeters thick.

Although it’s not physically impossible, like faster-than-light travel, or physically impractical, like Star Trek–style teleportation, brain mapping remains scientifically out of reach, but comfortably within the realm of science fiction. As for Denis the Carthusian, he reported making mental excursions into purgatory, during which he received revelations and conversed with souls. That experience is not unlike a Neuromancer hacker “jacking into” cyberspace and meeting avatars.

This essay by Charles Day first appeared on page 104 of the January/February 2013 issue of Computing in Science & Engineering, a bimonthly magazine published jointly by the American Institute of Physics and IEEE Computer Society.

Cosmic lobsters and electric bees

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Like other science editors I scan a lot of press releases. Some of the titles catch my eye, either because their writers opted for something witty or cute (“Sweeping the dust from a cosmic lobster”) or because the science in the press release, even when soberly summarized, is alluring (“New imaging device is flexible, flat, and transparent”).

A press release I encountered last Tuesday fell into the second category. “Sparks fly between flowers and bumblebees” flagged one of the papers previewed in Science magazine’s weekly press release. The notion that flowers have electrostatic fields and that bumblebees can detect the fields was so unexpected and intriguing that I promptly downloaded the paper.

As should be the case for papers in general science journals, the introduction proved to be accessible and informative. The authors, led by Daniel Robert of the University of Bristol in the UK, summarized evidence from the past 30 years that electricity plays a role in pollination.

A bumblebee caught in the act of collecting pollen from what looks like a lupin. CREDIT: Nigel Raine

A bumblebee caught in the act of collecting pollen from what looks like a lupin. CREDIT: Nigel Raine

My interest piqued, I wanted to read those early papers, especially one by Sarah Corbet, Jimmie Beament, and Dan Eisikowitch, which appeared in 1982 in volume 5 of Plant, Cell & Environment. Here is its abstract:

The measurements of Yes’kov & Sapozhnikov (1976) suggest that electrostatic potentials on foraging honeybees can reach hundreds of volts. Pollen grains of oilseed rape, Brassica napus L., subjected experimentally to potentials of this order, jumped a distance that increased approximately as the square of the voltage, between two pin electrodes on which, in some experiments, were impaled an anther or stigma of oilseed rape or a freshly-killed honeybee. Most floral surfaces were insulated, but there was a low-impedance path to earth via the stigma, and the electrostatic field due to an approaching charged bee must therefore concentrate there. Thus, if electrostatic potentials of this magnitude occur in nature they may increase the chance that pollen from bees will reach the stigma rather than other floral surfaces, as well as enabling pollen to jump from anther to bee and from bee to stigma across an air gap of the order of 0.5 mm.

As far as I can tell, the paper was the first to report that pollen is electrically charged. But I couldn’t evaluate its priority because the paper and others that Robert cited in his Science paper were behind their respective journals’ paywalls. That observation isn’t a criticism. Most of Physics Today‘s content is similarly walled off to nonsubscribers. Still, the paywalls did rather restrict my investigative efforts.

Sir James “Jimmie” William Longman Beament

But those efforts weren’t wholly in vain. My various online searches led me to John T. Green’s charming biographical memoir of his friend and former colleague, Jimmie Beament, the electric pollination pioneer.

Sir James “Jimmie” William Longman Beament (1921–2005) spent most of his productive and distinguished career at the University of Cambridge, where he had earned his bachelor’s degree. His first research project, and the one from which his career sprang, was to investigate the physical basis of insects’ ability keep their bodies from drying out.

Of course I can’t be sure, but it’s my hunch that if anyone had asked Beament why, in the 1940s, he was studying insect desiccation, he might have replied, “Because it’s interesting!” He couldn’t have known that he would go on to develop an insect-inspired wax that keeps bananas fresh on sea voyages, dispensing with the need for expensive refrigeration. Or that he’d solve the mystery of why tilapia weren’t finding enough food to eat in Ghana’s Lake Volta.

Beament was evidently so fascinated by the surfaces of insect bodies and eggs that he sought collaborations with physicists to study them. He was among the first entomologists to look at insects through an electron microscope. In 1958 he and Ken Machin, a radio astronomer, developed an electronic thermostat accurate to 0.01 K—and used it to discover, among other things, that locusts are coated with a wax that becomes permeable at 39 °C, thereby allowing evaporation to cool their muscles in very hot weather.

Soon after I read about Beament, I received a message from one of the fans of Physics Today‘s Facebook page. He sought my advice on whether he should pursue a graduate degree in materials science or physics. I told him he should choose a field in either discipline that would hold his interest through and after graduate school, just as Beament did.

Mind-reading computers

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EchoCharles275 Last year, the website of Britain’s Daily Mail newspaper became the world’s most-visited English-language news source. Although the Mail‘s website owes its popularity to a menu rich in celebrities, crime, and royals, it offers readers something that my stuffier hometown newspaper, the Washington Post, lacks: a top-level section devoted to science.

Granted, the Mail’s science coverage tends toward the sensational, but it does encompass superluminal neutrinos, the Higgs boson, and other weighty topics. The story that led the science section on 1 February 2012 was both sensational and important, as you can tell from the headline:

Mind-boggling! Science creates computer that can decode your thoughts and put them into words.

The story’s origin lies in an article published in PLoS Biology by Brian Pasley of the University of California, Berkeley, and his collaborators. Fifteen patients who suffered either epilepsy or brain cancer agreed to let Pasley’s team attach an array of electrodes to their brains while their skulls were opened for surgery. The electrodes recorded signals from neurons located in a part of the brain, the auditory cortex, that interprets spoken language.

Before the patients underwent surgery, they listened to single words and whole sentences. Pasley and his collaborators correlated the electrical recordings with the words’ acoustic spectra. A machine-learning algorithm then derived a mapping that could reproduce an acoustic spectrum from a neural recording.

Predicting what someone hears based on his or her brain activity is impressive, but it hardly qualifies as mind reading. However, it turns out that the auditory cortex is also responsible for encoding speech. When Pasley’s team asked each patient to think of words without uttering them, the algorithm accurately predicted what those unspoken words were. In that sense, the algorithm really did read the patients’ minds.

Pasley’s algorithm occupies one front in a broad campaign to understand how the human brain works. On another front, biophysicists are developing ways to map the topography of the brain’s interconnected neurons. Given that the human brain contains on the order of 1011 neurons, each of which is connected to up to 1000 other neurons, assembling a complete neuronal map could turn out to be infeasible—and perhaps unnecessary.

A detailed map of a single, characteristic neighborhood of the brain might yield enough information to identify the physical features that underlie thought and memory. But knowledge of those features alone might fall short of demonstrating that someone understands the brain. If that turns out to be the case, then a convincing demonstration might entail building a simulated brain.

The anatomy and physiology of such a brain wouldn’t necessarily resemble those of our own. Indeed, the first prototype could turn out to consist of a building-sized stack of optical tables where pulsed beams of light—the information-carrying signals—bounce off mirrors and pass through prisms. Provided that the simulated brain’s topology and interconnections are described using the same mathematical equations that apply to a human brain, such a demonstration would be valid.

And if that fantasy becomes a reality, simulation would have attained a new and higher status in science. Rather than providing a way to calculate a theory’s validation, the simulation would be the validation.

This essay by Charles Day first appeared on page 104 of the July/August 2012 issue of Computing in Science & Engineering, a bimonthly magazine published jointly by the American Institute of Physics and IEEE Computer Society.

When bits bite

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As the 1995 movie Species begins, space aliens have beamed to Earth information about a new, seemingly endless source of energy. The same transmission includes the codons for alien DNA and instructions for splicing them into the human genome.

The energy source proves bountiful, but the splicing, played out over the movie’s next 100 or so minutes, proves disastrous. Scientists construct the alien DNA, transfect it into a human egg cell, and watch as the egg develops with unnatural speed into a girl they name Sil. Alarmed by Sil’s rapid growth, the scientists plan to kill her, but she escapes and matures into a half-alien/half-human whose drive to mate and lack of inhibition combine in a gory rampage of sex and murder.

Reflecting on the movie one morning on my way to work, I thought, “That’s amazing—malevolent aliens could invade us with pure information!” Just the bits needed to encode DNA are enough to threaten human civilization. But a sequence of alien DNA, expressed as binary signal, is just that: a binary signal. It took unsuspecting humans to make the monster itself.

The idea that information is physical is hardly new. Although we can’t know for sure, marks pressed on wet clay or knots tied in string would have seemed more physical than not to ancient Babylonians and Incas. What’s more recent is the notion that information is intrinsically and inextricably physical. AT&T’s Claude Shannon, IBM’s Rolf Landauer, and others pioneered this viewpoint in the 1940s.

One of Landauer’s successors has shown that the physics of information has theological implications. Carlo Beenakker at the University of Leiden in the Netherlands usually theorizes about electron transport in structures that are just small enough for quantum coherence to play a role. But in a recent article, he tackled a problem raised 40 years ago by Carl Gustav Hempel: Where does physics stop and metaphysics begin?[1]

Beenakker’s analysis tools are limits derived by physicists. Information can’t be transferred faster than the speed of light (Albert Einstein), erased without generating kT log 2 of heat per bit (Landauer), or processed with available energy E faster than 4E/h operations per second (Norman Margolus and Lev Levitin). Beenakker asks three questions, among them, is the immortal soul physical or metaphysical? He answers,

In order to be physical, the immortal soul should contain and process information beyond death, which is the erasure of most information in the organism. Estimates of the amount of information lost upon death are in the order of 1032 per human. Mankind as a whole has lost some 1043 bits of information over the course of 50,000 years. We know of no mechanism by which this amount of information could have survived by physical means, leaving the immortal soul in the metaphysical domain.

Beenakker’s estimate for the duration of mankind comes from science: the age of our most recent chromosomal ancestor “Adam.” But his estimate of a human’s information content comes, indirectly, from science fiction: Lawrence Krauss derived it to conclude that the Star Trek transporters are infeasible.

Which is a relief. Otherwise, malevolent aliens could beam themselves to Earth, rather than just send us information about their DNA.

Reference

  1. C. Beenakker, “Hempel’s dilemma and the physics of computation,” Knowledge in Ferment: Dilemmas in Science, Scholarship and Society, A. Groen et al., eds., Leiden U. Press, Leiden, the Netherlands (2007), p. 65.

This essay by Charles Day first appeared on page 96 of the July/August 2007 issue of Computing in Science & Engineering, a bimonthly magazine published jointly by the American Institute of Physics and IEEE Computer Society.

Pretending to hypothesize

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For Physics Today‘s February 2003 issue, I wrote a news story about a paper in Physical Review Letters. In the paper, Dieter Braun and Albert Libchaber described how DNA molecules in solution, if confined in a small vessel and subjected to a steep temperature gradient, would form local concentrations that are 1000 times higher than in the rest of the vessel. The topic is potentially of monumental importance. High concentrations are needed for a primordial soup to beget the self-replicating molecular precursors of life—at least as we know it.

Now if you’d read the PRL paper before my PT story, you might have formed the impression that Braun and Libchaber set out to elucidate a physical mechanism that could have promoted the origin of life. Their clear, methodical description suggested, but did not state, that they were testing a hypothesis.

In fact, as I found out when I interviewed him, Braun stumbled on the effect as a byproduct of a quite different experiment to do with the nonequilibrium heating of reactants. The accidental nature of the discovery is absent from the PRL, where it might have been a distraction, but present in my story, where it added dramatic interest.

Among McNeill Alexander’s research interests is the storage and release of energy in the muscles and tendons of kangaroos and other mammals. CREDIT: Chris Samuel

Braun and Libchaber’s discovery came to mind yesterday when I encountered a paper by Darrell Rowbottom and McNeill Alexander, which appears in the latest issue of Science in Context. Rowbottom is an associate professor of philosophy at Lingnan University, a public liberal arts college in Hong Kong. Alexander is a professor emeritus of biology at Leeds University in England. Together they sought to determine how often research papers in Alexander’s field, biomechanics, are framed as tests of hypotheses.

Why would anyone embark on such an investigation you might ask. The paper’s introduction hints at an answer. Alexander recounts what comes across—at least to me—as a troubling remark about funding from a fellow biomechanicist. The unnamed colleague told Alexander that he did hypothesis-driven research because that’s what the UK’s Biotechnology and Biological Sciences Research Council favors. “No hypothesis, no money” was the implication.

Some philosophers of science and some scientists regard the testing of hypotheses as the epitome of the scientific method, especially when it entails predicting a previously unmeasured phenomenon. A prime example is Arthur Eddington’s 1919 verification of the bending of starlight by the Sun’s gravity, a prediction of Albert Einstein’s theory of general relativity.

On the other hand, physicists and other scientists value curiosity-driven research. Indeed, the list of physics Nobel laureates abounds in people who were looking for something that they thought might be interesting but who weren’t testing a carefully formulated hypothesis. The most recent laureates, Saul Perlmutter, Adam Riess, and Brian Schmidt, were surprised by their discovery of dark energy.

Presentational hypotheses

Biologists, note Rowbottom and Alexander, tend to favor hypothesis testing, whereas physicists are more tolerant of open-ended investigations or, to use the perjorative term, “fishing expeditions.” Which group would biomechanists, who apply physics to biology, most resemble?

To find out, Rowbottom and Alexander looked at 50 papers each from the Journal of Experimental Biology and the Journal of Biomechanics. All the papers were drawn from single volumes published in 2007 and 2008. They classified the papers as H (actually testing a hypothesis), E (exploratory; not testing a hypothesis), P (presenting a hypothesis but not really testing one), and S (suspected of presenting a hypothesis but not really testing one). A fifth category O (for “other”) accounted for papers that couldn’t be clearly assigned to one of the other four categories.

If the P category seems odd, consider this example. In their J Exp. Bio. paper, Maria Almbro and Cecilia Kullberg sought to test “whether the flight performance of an insect . . . is affected by variation in body mass due to feeding.” But according to Rowbottom and Alexander, the authors, by their own admission, already knew that sated and starving insects (butterflies, in fact) fly differently. Even though Almbro and Kullberg presented their research as hypothesis testing, what they were actually doing, argue Rowbottom and Alexander, was measuring a known effect.

In all, Rowbotton and Alexander found that 58% of the papers purported to test hypotheses, of which two thirds really did. The remaining third used, or were suspected of using, hypothesis testing solely as a presentational device. Not one of the 100 papers was classified as E for exploratory. Summarizing their findings, Rowbottom and Alexander write:

Overall, therefore, it is reasonable to conclude that biomechanists have a bias towards presenting their research as testing hypotheses, and (especially) prefer not to present their research as if it bears no relation to hypothesis testing. Needless to say, this could be mainly pragmatic, rather than reflect widespread agreement on what counts as good scientific practice (or genuine scientific activity). If biomechanists suspect that their chances of publication (and/or funding) will be increased by presenting their work in a particular way, then many will do so even if doing so is inaccurate.

I find Rowbottom and Alexander’s findings somewhat shocking. Although I can’t be sure, I think that Braun and Libchaber omitted the serendipitous nature of their research for the sake of clarity. Their presentation certainly helped me understand what they’d measured. However presented, their results stand by themselves.

But it would damage science if a bias against exploratory research in biomechanics and in the rest of biology stifled not only the presentation of research but also its practice. Before Rowbottom and Alexander started their investigation, Alexander asked 11 “well-regarded biomechanists with a range of experience” to categorize what they considered to be their best three papers. Fifteen percent were fishing expeditions.

Hydra, fruit flies, and stripy colonies of bacteria

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In 1952, two years before his untimely death at the age of 41, the mathematician Alan Turing wrote an influential paper entitled “The Chemical Basis of Morphogenesis.” The paper tackled the problem of how limbs and other structural patterns arise in plants and animals that begin life as undifferentiated blobs of cells.

Turing’s mechanism relies on the competition between a slow-diffusing chemical—a morphogen—that activates a reaction and a fast-diffusing chemical that inhibits the reaction. Nudging the reaction-diffusion system into a metastable state yields stable stripes, spots, and other patterns.

Judging by his paper’s abstract, Turing was inspired, in part, by Hydra, a genus of simple, water-dwelling animals whose body plan consists of a single sticky foot, a stem, and 1–12 thin, neurotoxin-charged tentacles. Although his mechanism presumes a continuous, two-dimensional system, its basic premise—that pattern development is controlled by the concentration-dependent diffusion and inhibition of signaling molecules—is observed in three-dimensional, multicellular systems, notably in biologists’ favorite fly, Drosophila melanogaster.

In common with other signaling molecules, morphogens initiate a complex chain of biochemical steps. For a flavor of that complexity, here’s how the University of Tokyo’s Testuya Tabata and Yuki Takei described the action of one Drosophila morphogen, Dpp, in a primer published in 2004:

The pathway that transduces the Dpp signal involves a combination of two types of serine/threonine kinase receptors, type I and type II. The activated type I receptor phosphorylates cytoplasmic transducers, so-called receptor-regulated Smads (named after the first-identified members of this family: Sma in C. elegans and Mad in Drosophila), which, upon phosphorylation, translocate into the nucleus and regulate the expression of target genes (Fig. 4A). In Drosophila wing development, Thickveins (Tkv) acts as a type I receptor; its constitutively active form (Tkv*), when ectopically expressed, can induce the expression of the target genes sal and omb (Fig. 4).

Each step in the Dpp pathway provides an opportunity for regulation, thereby helping to ensure that a larval fruit fly stays on course to develop properly functioning wings. Given the high biological stakes—a fly with malformed wings can’t feed or breed—the complexity of the Dpp pathway is understandable and evolutionarily inevitable.

A paper published today in Science is noteworthy because it demonstrates a simpler, albeit artificial, route for pattern formation in a multicellular system. Jian-Dong Huang of the University of Hong Kong, Terence Hwa of the University of California, San Diego, and their collaborators genetically modified Escherichia coli so that the single-celled organism would lose its mobility when crowded with other cells from the same mutant strain. Left to proliferate at the center of a nutrient-rich dish, colonies of the mutant spontaneously formed stable, concentric stripes of alternating high and low density.

The genetic engineering that underlay the pattern formation involved three basic steps:

  • Appropriating the density-sensing gene from another bacterium, Vibrio fischeri. Once equipped with the gene, the mutant E. colibacteria made and excreted a small molecule called AHL when they crossed a density threshold.
  • Controlling E.coli‘s mobility. Usually, when an E. coli bacterium senses a gradient in the concentration of a nutrient, it swims up the gradient. When it can’t sense a gradient, it stops, momentarily tumbles, then swims off in a different, random direction. Knocking out a gene called cheZ deprives E. coli of its ability to swim. The Huang–Hwa team modified the genome of their E. coli so that cheZwould be suppressed in the presence of a molecule called CI.
  • Linking density-sensing to mobility. Another modification caused CI to be synthesized in the presence of AHL, the molecule secreted when the mutant E. coli is crowded.

The stripes result from the bacteria’s density-dependent mobility. As a colony starts consuming nutrient and proliferating, the density of bacteria in the center rises and a front of low-density bacteria expands from the center into fresh nutrient. At the center, the proliferating bacteria cross the density threshold at which AHL, through the secretion of CI and the suppression of cheZ, deprives the bacteria of their swimming ability. Those central bacteria still eat and proliferate. As they do so, their density continues to rise until the nutrient is exhausted. The upshot is stable circular patch of high bacterial density.

Periods400.jpg

The bacteria just beyond the central patch are still mobile. Some of them move inward and become trapped; others move outward, remain mobile, and create a second high-density region behind the still-expanding front. As before, when the nutrient runs out, a stable patch of high bacterial density is left behind—this time in the shape of ring. Between the two high-density regions lies a stable low-density region that marks the zone where inward- and outward- moving bacteria met different fates. The creation of ring-shaped stripes continues until the front reaches the edge of the dish and the nutrient runs out.

By formulating a mathematical model of stripe formation, the Huang–Hwa team could predict the conditions under which stripes form and whether they form at all. And by adding an extra genetic modification, one that allows the suppression of cheZ to be tuned, the researchers could test their model. It passed.

The Huang–Hwa team closes its paper by noting that the formation of stripy colonies of bacteria suggests that periodic structures can form autonomously in individual organisms without the intervention of a biological clock. To me, the stripy colonies suggest something else: That the complex pattern formation mechanisms in Drosophila and other higher organisms evolved from something akin to the genetically engineered mechanism in the bacteria.

Charles Day

Let’s talk about lampreys!

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Lampreys look like eels, but they’re anatomically simpler than other fish. Lacking jaws, lampreys instead have sucker-like mouths lined with concentric rings of teeth. The likelihood that lampreys are the closest surviving descendant of the first vertebrate has motivated numerous studies, including some that involve physics.

lampreymouth.jpg

My first encounter with lampreys was in 2004. For Physics Today‘s June issue of that year I wrote a news story about the UV-sensing ability of the lamprey’s pineal gland. All vertebrates have pineal glands. Ours is about the size of a lentil and sits deep inside our brain. Its principal function appears to be the secretion of the hormone melatonin, which regulates circadian rhythms.

The lamprey’s pineal lies close to the top of its head—close enough to directly sense light. Biologists knew since the 1960s that the lamprey’s pineal could sense UV. In 2003 Kyoto University’s Mitsumasa Koyanagi and his colleagues set about trying to find out what the lamprey does with its UV-sensing ability.

Using a mix of methods drawn from biochemistry, genetic engineering, and spectroscopy, Koyanagi and his colleagues discovered that the lamprey’s pineal gland contains an unusual bistable pigment. The pigment’s bistability enables the lamprey to sense the ratio of visible to UV light. Because that ratio varies with depth in water, Koyanagi speculated that the pineal helps the lamprey gauge its depth.

Thymus-like organs

I noticed more lamprey-related research earlier this month. Thomas Boehm of the Max Planck Institute of Immunobiology and Epigenetics in Freiburg, Germany, and his colleagues found strong evidence that lampreys have thymus-like organs in their gills.

If confirmed, the finding is significant because it could shed light on the evolution of our immune systems. Unlike other animals, vertebrates have an adaptive immune system that continuously trains pathogen-killing T-cells to respond to new threats. The thymus is where the training takes place. Lampreys have a simple version of the adaptive immune system but before Boehm’s work no one had identified a lamprey organ that resembles the thymus.

My curiosity roused, I looked for the latest research on lamprey ancestry and turned up a paper from last fall. A team led by Philip Donoghue of Dartmouth Medical School in New Hampshire and Kevin Peterson of Bristol University in the UK analyzed the genetic sequences of the microRNAs found in lampreys and in another kind of jawless fish, the hagfish.

Known as phylogenetics, the statistical analysis of DNA and RNA exploits techniques such as Bayesian inference and Markov chain Monte Carlo that are used and in some cases were invented by physicists.

When Donoghue, Peterson, and their collaborators compared the microRNAs of lampreys and hagfish with each other and with other fish, they made two interesting discoveries. First, lampreys and hagfish are branches of the same evolutionary tree, not separate branches as some biologists had argued.

Second, the anatomical simplicity of lampreys and hagfish is not the result of their being more closely related to a primitive ancestor than sharks, cod, and other fish are. Rather, the simplicity results from the jawless fish having lost features and functions over time, just as snakes lost their limbs.

Intriguingly, it now looks as though the closest common ancestor to all today’s vertebrates was more, not less, complex than the lamprey.

Charles Day

Photoreceptors, carburetors, and intelligent design

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A paper in today’s Nature caught my eye. E. J. Chichilnisky of the Salk Institute for Biological Studies in San Diego and his collaborators set out to determine how the cells in primate retinas are wired to sense color.

Now you might think, as I did before reading the paper, that the problem had already been solved. Our retinas contain three types of photoreceptive neuron that are maximally sensitive to red, green, or blue light. When, say, the blue photoreceptors fire, we see blue, right? Wrong.

It turns out that neuroscientists have known for some time that our brains don’t receive direct signals from the R, G, and B photoreceptors. That’s in part because the photoreceptors’ spectral responses overlap. A dim red light would elicit the same level of response in an R photoreceptor as a bright red light would elicit in a G photoreceptor.

Our eyes rely instead on “opponency.” The signals that run from our retinas to our brains correspond to two opposing combinations: B − (R + G) and R − G. The combinations are calculated by specialized neurons called ganglions that receive input from mixed groups of photoreceptors.

Chichilnisky and his team connected hundreds of ganglion cells in vitro to electrodes. They then recorded the cells’ response to a spectrally varying light field whose spatial resolution was fine enough to trigger responses in individual photoreceptors.

opponency.jpg

The figure shows schematically how the photoreceptors (colored dots) are grouped to feed data to individual ganglions (at the focal points of the white lines). In principle, the grouping of randomly distributed photoreceptors could account for the retina’s sensitivity to color. But Chichilnisky found that an extra ingredient is needed: The photoreceptors closest to the focal points are weighted more heavily than those farther out.

Sensing color with randomly distributed and simply connected R, G, and B photoreceptors seems elegant, but if you look under the hood at the proteins responsible, you see a baroque edifice of bizarre complexity. Here, for you to skip, skim, or scrutinize, is how the Wikipedia entry on photoreceptors describes the protein-to-protein transduction chain:

  1. The rhodopsin or iodopsin in the outer segment absorbs a photon, changing the configuration of a retinal Schiff base cofactor inside the protein from the cis-form to the trans-form, causing the retinal to change shape.
  2. This results in a series of unstable intermediates, the last of which binds stronger to the G protein in the membrane and activates transducin, a protein inside the cell. This is the first amplification step – each photoactivated rhodopsin triggers activation of about 100 transducins. (The shape change in the opsin activates a G protein called transducin.)
  3. Each transducin then activates the enzyme cGMP-specific phosphodiesterase (PDE).
  4. PDE then catalyzes the hydrolysis of cGMP. This is the second amplification step, where a single PDE hydrolyses about 1000 cGMP molecules. (The enzyme hydrolyzes the second messenger cGMP to GMP.)
  5. With the intracellular concentration of cGMP reduced, the net result is closing of cyclic nucleotide-gated ion channels in the photoreceptor membrane because cGMP was keeping the channels open. (Because cGMP acts to keep Na+ion channels open, the conversion of cGMP to GMP closes the channels.)
  6. As a result, sodium ions can no longer enter the cell, and the photoreceptor hyperpolarizes (its charge inside the membrane becomes more negative). (The closing of Na+channels hyperpolarizes the cell.)
  7. This change in the cell’s membrane potential causes voltage-gated calcium channels to close. This leads to a decrease in the influx of calcium ions into the cell and thus the intracellular calcium ion concentration falls.
  8. The lack of calcium means that less glutamate is released to the bipolar cell than before (see below). (The decreased calcium level slows the release of the neurotransmitter glutamate, which can either excite or inhibit the postsynaptic bipolar cells.)
  9. Reduction in the release of glutamate means one population of bipolar cells will be depolarized and a separate population of bipolar cells will be hyperpolarized, depending on the nature of receptors (ionotropic or metabotropic) in the postsynaptic terminal (see receptive field).

Evolution and the limits of what can be achieved within cells with proteins are behind the rather involved transduction chain. To achieve its current performance, the primate eye has made use of a succession of incremental changes that began in the Cambrian era 540 million years ago.

Human engineers aren’t limited to making only incremental changes. My first car, a 1977 Chevrolet Malibu, had a bulky—and balky—carburetor to mix petrol and air. My second (and current) car, a 1993 Honda Civic, has a fuel injector to do the same job.

The fuel injector didn’t evolve from the carburetor, nor did the transistor evolve from the thermionic valve. Both innovations, which are simpler and more effective than their predecessors, resulted from leaps of engineering and scientific imagination—which brings me, at last, to my main point.

The devices in our bodies are intricate and complex, but they’re too fussy to be the work of an intelligent designer.

Charles Day